IBM Big Data Hub
JANUARY 5, 2023
Poor data quality is one of the top barriers faced by organizations aspiring to be more data-driven. Ill-timed business decisions and misinformed business processes, missed revenue opportunities, failed business initiatives and complex data systems can all stem from data quality issues.
Ontotext
FEBRUARY 12, 2024
In the final part of this three-part series, we’ll explore ho w data mesh bolsters performance and helps organizations and data teams work more effectively. Usually, organizations will combine different domain topologies, depending on the trade-offs, and choose to focus on specific aspects of data mesh.
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Cloudera
JULY 29, 2022
Corporations are generating unprecedented volumes of data, especially in industries such as telecom and financial services industries (FSI). However, not all these organizations will be successful in using data to drive business value and increase profits. Read on to be sure you set yourself up for success. .
IBM Big Data Hub
FEBRUARY 9, 2023
In our last blog , we delved into the seven most prevalent data challenges that can be addressed with effective data governance. Today we will share our approach to developing a data governance program to drive data transformation and fuel a data-driven culture. Don’t try to do everything at once!
Cloudera
SEPTEMBER 19, 2023
Adding another position may not be terribly appealing, but there is one C-suite role every company should consider—chief data and analytics officer (CDO or CDAO). The CDO is an essential role in a data-driven organization. Without a data champion, the C-suite can overlook and even ignore data.
Cloudera
JANUARY 5, 2023
In the past year, businesses who doubled down on digital transformation during the pandemic saw their efforts coming to fruition in the form of cost savings and more streamlined data management. Here are three key trends that will likely dominate the priorities of APAC’s business leaders in the coming year.
IBM Big Data Hub
JUNE 30, 2022
The rise of data strategy. There’s a renewed interest in reflecting on what can and should be done with data, how to accomplish those goals and how to check for data strategy alignment with business objectives. The evolution of a multi-everything landscape, and what that means for data strategy.
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